The landscape of oncology drug development is rapidly changing with the introduction of immune-targeting therapies. Specifically, recent approvals of monoclonal antibodies that target Programmed Death Receptor (PD-1), Programmed Death Ligand 1 (PD-L1) and other immune checkpoints have demonstrated durable clinical benefit across a range of tumor indications. Unfortunately, clinical benefit is limited to a small fraction of patients highlighting the urgent need for predictive biomarkers capable of identifying patients most likely to benefit and prevent needless exposure to therapies with associated high costs and potential of adverse autoimmune effects.
Currently, the overexpression of PD-L1 has been identified as a predictive biomarker for the response to PD-1/PD-L1 targeting antibodies. However, detection of PD-L1 expression by IHC is a controversial predictive biomarker of which patients may benefit from therapy. Several factors have been attributed to why PD-L1 immunohistochemical (IHC) staining is limited in its predictive ability. For example, IHC detection methods are sometimes unreliable. PD-L1 expression is determined using an anti-PD-L1 antibody by IHC staining of formalin-fixed paraffin-embedded tumor tissue. Staining is confounded by variable technical factors including pre-analytical factors (proper tissue collection, handling, preservation & storage); analytical factors (tissue section thickness, tumor content, staining on non-tumor cells; spatial & temporal limitations of the tissue) and post-analytical factors (operation bias in assessing staining intensity; lack of harmonization in procedures and cut-offs with the 5 available PD-L1 companion diagnostic IHC assays). In addition, there is both intra and inter-patient heterogeneity of PD-L1 expression within a given specimen as well as between the primary and metastatic lesion. Finally, PD-L1 expression is dynamic and can be induced by activated antigen-specific T cells, therapeutics and cytokines within the tumor microenvironment illustrating that evaluation of a single time point may not be reflective of the current responsive state of a tumor to PD-1/PD-L1 targeting therapy.
Recently, tumor mutational burden (TMB) (i.e., the total number of mutations per coding area of a tumor genome) has emerged as a biomarker of response to anti-PD-1 therapy. Using whole-exome sequencing of non-small cell lung cancers treated with pembrolizumab, higher nonsynonymous mutation burden in tumors was associated with improved objective response, durable clinical benefit, and progression-free survival. However, despite the promise of TMB, there are reported cases where patients with high TMB fail to respond to PD-1/PD-L1 targeting therapy as well as patients with low TMB responding to check point inhibitor therapy.
Other methods, including non-invasive methods, for predicting response to immune checkpoint inhibitors such as anti-PD-1 or anti-PD-L1 antibodies are therefore needed.